Results 21 to 30 of about 12,132 (264)

Adaptive Sparse Grid Classification Using Grid Environments [PDF]

, 2007
Common techniques tackling the task of classification in data mining employ ansatz functions associated to training data points to fit the data as well as possible. Instead, the feature space can be discretized and ansatz functions centered on grid points can be used.
Dirk Pflüger, Ioan Lucian Muntean, Hans-Joachim Bungartz   +2 more
openaire   +1 more source

Fast deconvolved beamforming for arbitrary arrays based on off-grid sparse Bayesian learning [PDF]

JASA Express Letters
The deconvolved beamforming (dCv) improves spatial resolution without expanding the array aperture but fails for the shift-variant beam pattern and the real targets, which are not located on the sampling grids.
Jianli Huang, Yu Wang, Zaixiao Gong, Haiqiang Niu, Jun Wang, Haibin Wang   +5 more
doaj   +1 more source

Orthogonal polynomial expansions on sparse grids

Journal of Complexity, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yanzhao Cao, Ying Jiang 0002, Yuesheng Xu   +2 more
openaire   +1 more source

Sparse Grids for the Vlasov–Poisson Equation [PDF]

, 2016
The Vlasov–Poisson equation models the evolution of a plasma in an external or self-consistent electric field. The model consists of an advection equation in six dimensional phase space coupled to Poisson’s equation. Due to the high dimensionality and the development of small structures the numerical solution is quite challenging.
Kormann, K., Sonnendrücker, E.
openaire   +2 more sources

An Improved Compressive Sensing and Received Signal Strength-Based Target Localization Algorithm with Unknown Target Population for Wireless Local Area Networks

Sensors, 2017
In this paper a two-phase compressive sensing (CS) and received signal strength (RSS)-based target localization approach is proposed to improve position accuracy by dealing with the unknown target population and the effect of grid dimensions on position ...
Jun Yan, Kegen Yu, Ruizhi Chen, Liang Chen   +3 more
doaj   +1 more source

Large-scale crop mapping from multi-source optical satellite imageries using machine learning with discrete grids

International Journal of Applied Earth Observations and Geoinformation, 2021
The spatial distribution of crops is an important agricultural parameter, which is used to derive important information about crop productivity and food security.
Shuai Yan, Xiaochuang Yao, Dehai Zhu, Diyou Liu, Lin Zhang, Guojiang Yu, Bingbo Gao, Jianyu Yang, Wenju Yun   +8 more
doaj   +1 more source

Finite Differences on Sparse Grids for Continuous-Time Heterogeneous Agent Models

Algorithms
We present a finite difference method working on sparse grids to solve higher dimensional heterogeneous agent models. If one wants to solve the arising Hamilton–Jacobi–Bellman equation on a standard full grid, one faces the problem that the number of ...
Jochen Garcke, Steffen Ruttscheidt
doaj   +1 more source

A Hierarchical Routing Scheme With Load Balancing in Software Defined Vehicular Ad Hoc Networks

IEEE Access, 2018
The vast majority of routing approaches for vehicular ad hoc networks (VANETs) are distributed, which are ineffective to exploit the global networking information and easily lead to local optimum, appearing as sparse connectivity and network congestion ...
Yangshui Gao, Zhilong Zhang, Dan Zhao, Yi Zhang, Tao Luo   +4 more
doaj   +1 more source

Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones

Advanced Engineering Materials, EarlyView.
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell, Martha Leach, Hongtao Song, Carolyn Seepersad   +3 more
wiley   +1 more source

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source